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Documentwhat value added one get from diff visualization methods for association
: DBSCAN – uniqueness, applications and limitations
What analytical elements one should consider when running empirical analysis with association rules
What are the most important steps in basket analysis with association rules?
How to compare MDS, PCA and hierarchical trees?
Applications of hierarchical models – what for do we need trees?
Factors to consider when applying sensitivity analysis of PCA results
Factors to consider when applying sensitivity analysis of MDS results
Similarities and differences between MDS and PCA
Possible applications of clustering – thematic areas, data characteristics, pros and cons
How Clustering Works with Colours and Images
Pre and post diagnostics in clustering
Overview of available packages for clustering methods – classes, results, switching possibilities
Similarities and differences of k-means, PAM and CLARA
Dimensionality Reduction
Association Rules Mining
Customers Segmentation using Clustering